1. Field of the Invention
This invention relates generally to the field of semiconductor device manufacturing and, more particularly, to a method and apparatus for fault detection using multiple tool error signals.
2. Description of the Related Art
There is a constant drive within the semiconductor industry to increase the quality, reliability and throughput of integrated circuit devices, e.g., microprocessors, memory devices, and the like. This drive is fueled by consumer demands for higher quality computers and electronic devices that operate more reliably. These demands have resulted in a continual improvement in the manufacture of semiconductor devices, e.g., transistors, as well as in the manufacture of integrated circuit devices incorporating such transistors. Additionally, reducing the defects in the manufacture of the components of a typical transistor also lowers the overall cost per transistor as well as the cost of integrated circuit devices incorporating such transistors.
Generally, a set of fabrication steps is performed on a lot of wafers using a variety of tools, including photolithography steppers, etch tools, deposition tools, polishing tools, rapid thermal processing tools, implantation tools, etc. The performance of the fabrication steps is also typically measured by metrology tools, such as scanning electron microscopes, optical measurement tools, electrical test tools, etc. The technologies underlying semiconductor fabrication and metrology tools have attracted increased attention over the last several years, resulting in substantial refinements. However, despite the advances made in this area, many of the tools that are currently commercially available suffer certain deficiencies. In particular, such tools often lack advanced process data monitoring capabilities, such as the ability to provide historical parametric data in a user-friendly format, as well as event logging, real-time graphical display of both current processing parameters and the processing parameters of the entire run, and remote, i.e., local site and worldwide, monitoring. These deficiencies can engender nonoptimal control of critical fabrication or metrology parameters, such as throughput, accuracy, stability and repeatability, fabrication temperatures, mechanical tool parameters, wafer state measurements/results, and the like. This variability manifests itself as within-run disparities, run-to-run disparities and tool-to-tool disparities that can propagate into deviations in product quality and performance, whereas an ideal monitoring and diagnostics system for such tools would provide a means of monitoring this variability, as well as providing means for optimizing control of critical parameters.
One technique for improving the operation of semiconductor processing line includes using a factory wide control system to automatically control the operation of the various fabrication and metrology tools. The manufacturing tools communicate with a manufacturing framework or a network of processing modules. Each tool is generally connected to an equipment interface. The equipment interface is connected to a machine interface which facilitates communications between the tool and the manufacturing framework. The machine interface can generally be part of an advanced process control (APC) system. The APC system initiates a control script based upon a manufacturing model, which can be a software program that automatically retrieves the data needed to execute a manufacturing process. Often, semiconductor devices are staged through multiple tools for multiple fabrication processes and associated metrology measurements, generating data relating to the quality of the processed semiconductor devices.
During the fabrication process various events may take place that affect the performance of the devices. That is, variations in the fabrication steps result in device performance variations. Factors, such as feature critical dimensions, doping levels, contact resistance, particle contamination, etc., all may potentially affect the end performance of the device. Various tools in the processing line are controlled in accordance with performance models to reduce fabrication and metrology measurement variation. Commonly controlled tools include photolithography steppers, polishing tools, etching tools, and deposition tools. Pre-processing and/or post-processing metrology data is supplied to process controllers for the tools. Operating recipe parameters, such as processing time, are calculated by the process controllers based on the performance model and the metrology information to attempt to achieve post-processing results as close to a target value as possible. Reducing variation in this manner leads to increased throughput, reduced cost, higher device performance, etc., all of which equate to increased profitability.
Statistical process control techniques are commonly used to monitor the operation of manufacturing processes, systems, or individual tools. Commonly, various measurements related to the process being monitored are compiled and plotted on a control chart. The control chart has control limits, which, if violated, immediately indicate an error condition requiring investigation. Certain error conditions result from special causes, such as a defective tool, operator error, material defect, process changes, trends, etc., that may be corrected by process optimization or redesign.
In some instances error conditions are present, yet go undetected. The error signal may not be significantly strong to rise above the threshold set for detection. An error signal may also be masked by measurement detection limitations and noise. Undetected faults can lead to misprocessed wafers, which require rework or may even need to be scrapped. Misprocessed wafers are costly and reduce the efficiency of the processing line.
The present invention is directed to overcoming, or at least reducing the effects of, one or more of the problems set forth above.
One aspect of the present invention is seen in a method for detecting faults in a manufacturing line. The method includes processing a plurality of workpieces in a plurality of tools; generating a first error signal associated with the workpieces based on the processing performed in a first tool of the plurality of tools; generating a second error signal associated with the workpieces based on the processing performed in a second tool of the plurality of tools; combining the first and second error signals to generate a composite error signal; and identifying a fault condition with the workpieces based on the composite error signal.
Another aspect of the present invention is seen in a manufacturing system including a plurality of tools adapted to process workpieces, and a fault monitor. The fault monitor is adapted to receive a first error signal associated with the workpieces based on the processing performed in a first tool of the plurality of tools, receive a second error signal associated with the workpieces based on the processing performed in a second tool of the plurality of tools, combine the first and second error signals to generate a composite error signal, and identify a fault condition with the workpieces based on the composite error signal.